ECE:5845 Modern Databases - Final Project

Samuel Nicklaus, Cole Arduser, Colin Hehn

Link to dataset here.

Note that the dataset we used has been heavily modified to meet our needs. For the full data, please refer to the university phpadmin student18 account under the final_project schema

Project README

Overview

This project is a comprehensive application leveraging Python, Flask, Neo4j, and the Graph Data Science (GDS) library version 4.4.28. It is designed to utilize the powerful features of these technologies, offering a robust backend system with advanced data processing and graph database capabilities.

Prerequisites

Before setting up the project, ensure that you have the following prerequisites installed on your system:

1. Python: Ensure you have Python 3.x installed. You can download it from python.org.

2. Neo4j: A highly scalable native graph database, which allows for efficient management and querying of connected data. Download and install Neo4j from neo4j.com.

3. Graph Data Science (GDS) Library 2.5.5: A library for Neo4j, enabling advanced analytics and machine learning on graphs. Ensure that you are using GDS version 2.5.5, compatible with your Neo4j version. Refer to the Neo4j GDS installation guide for detailed instructions.

Setup and Installation

Neo4j Setup

1. See the project directory for 'tjr_neo4j_server.dump'. This is a backup of the Neo4J server we used locally to provide recommendation data for our project.
2. See this guide for instructions on how to construct a new DBMS from a dump file. The instructions provided conduct it through the Neo4J Desktop application, but it can also be done through the command line.
3. Ensure that the Neo4J DB you created is version 4.4.28, and that the GDS library (version = 2.5.5) is installed and enabled.
4. Launch the Neo4J DBMS in the GUI, and ensure it is live before you run the Recommendation Engine application.

Python and Flask Server (Windows Only)

1. Create a .env file inside the flask_server directory, and add the following to it:

   POSTGRES_HOST=s-l112.engr.uiowa.edu
   POSTGRES_PASSWORD=finalproject2023
   POSTGRES_USER=mdb_student18
   
   NEO4J_URI=bolt://localhost:7687 or whatever you set it to
   NEO4J_USER=neo4j or whatever you set it to
   NEO4J_PASSWORD=password or the password you set for the Neo4J DBMS

2. To run the Flask server, navigate to the flask_server directory and run the following command:

   .\dist\app.exe

3. The server will be running on localhost:5000. You can now use the client application to interact with the server.

4. If the executable does not work, start a virtual environment and pip install the requirements with the following command:

   pip install -r requirements.txt

5. Then run the following command to start the server:

   python app.py

Running the Client Application

Prerequisites

• Node.js (which comes with npm)

Installation

1. navigate to the directory:

   cd client
   

2. To install the project dependencies, run the following command:

   npm install
   

Running the Application

1. To start the development server, use the following command:

   npm run dev
   

General Configuration and IDE Settings

• .idea/ directory containing various configuration files for JetBrains IDEs.

Client Application

• Client/ directory with Vue.js application files:
  • Configuration files like .eslintrc.cjs, .prettierrc.json, and package.json.
  • Source code in Client/src/App.vue.
  • Static assets in Client/src/assets/.
  • HTML entry point Client/index.html.
  • Vite configuration in Client/vite.config.js.

Dataset

• DATASET/ directory with CSV files (Company.csv, Job.csv, Review.csv, etc.) and Python scripts (add_job_id.py, demo.py).

Flask Server

• flask_server/ directory containing Python files for Flask server (app.py, neo4j_db.py, postgres_db.py) and a requirements.txt file for dependencies.
• Compiled files and build artifacts in flask_server/build/.

Miscellaneous

• Root directory files like README.md, dataAvg.py, and a Neo4j dump file tjr_neo4j_server.dump.